Multiomics profiling and association with molecular and immune features in association with benefits from immunotherapy for patients with previously treated stage IV or recurrent squamous cell lung cancer from the phase III SWOG LungMAP S1400I trial.
Authors: Edwin R. Parra, Dzifa Yawa Duose, Jiexin Zhang, Mary Weber Redman, Rossana Lazcano Segura, Mario L. Marques-Piubelli, Caddie Laberiano Fernandez, BaiLi Zhang, James Lindsay, Radim Moravec, Kasthuri Kannan, Rajyalakshmi Luthra, Gheath Alatrash, Roy S. Herbst, Ignacio Ivan Wistuba, Scott N. Gettinger, Lyudmila Bazhenova, J. Jack Lee, Jianjun Zhang, Cara L. Haymaker
Journal: Journal of Clinical Oncology (2022)

9046 Background: Immune checkpoint blockade (ICB) has become a standard pillar of treatment for lung cancer. However, only ̃20% of unselected patients can achieve durable clinical benefits. We performed immunogenomic profiling of tissue specimens from a randomized Phase III trial S1400I on metastatic lung squamous cell carcinoma (SCC) to evaluate if there were factors associated with better prognoses with ICB from single-agent versus combined targeting PD-1/CTLA-4 and evaluate if any differentiated between the treatments. Methods: We utilized FFPE tumor tissue submitted for Lung-MAP screening provided by the SWOG bank. SCC samples from 82 eligible patients treated with combined nivolumab+ipilimumab (N+I) or single agent nivolumab (N) were subjected to multiplex immunofluorescence (mIF, n = 82) and NanoString (ncounter PanCancer Immune Profiling Panel, n = 32). Cell density phenotypes (cells/mm2) were defined using image analysis of staining for cytokeratin, CD3, CD8, granzyme B, CD45RO, FOXP3, PD1, PD-L1, and CD68. Immunogenomic features were associated with response, PFS, and OS derived from data provided by the LungMap team to the CIDC portal. For statistical analyses, non-parametric tests were utilized to assess associations of cell phenotypes versus continuous or categorical variables, and log-rank test analysis was performed to identify cell phenotypes or genes correlated with survival. Results: In both arms higher densities of total CD3+CD45RO+ T cells ( P= 0.041), CD3+PD-1+ T cells ( P= 0.024) and CD3+CD8+PD-1 T cells in stroma ( P= 0.042) and CD3+CD8+GZMB+ T cells in the tumor compartment ( P= 0.011) were positively associated with PFS. In the N+I arm but not in the N arm, higher densities of CD3+CD8+GZMB+ T cells in the tumor compartment were associated with better PFS ( P= 0.015) and higher densities of stroma CD3+CD8-FOXP3+ T cells with worse OS. Spatial analysis showed that the presence of CD8+GZMB+ T cells close to malignant cells (median, ≤19.27 µm) was associated with better PFS ( P= 0.037) in N+I arm and cluster analysis showed low clustering of cells in TMB-high vs. TMB-low tumors (P &lt; 0.01). Gene expression profiling demonstrated that myeloid infiltration, immune recruitment, and inflammation genes were associated with a positive clinical outcome ( P&lt; 0.05). In both arms, BLNK, CD163, FCGR2A were associated with better OS ( P&lt; 0.01), IRF1 and BLNK were associated with increased PFS ( P&lt; 0.01). In the N+I arm but not in the N arm, we observed significantly higher CD45 immune cell scores, including CD8 T cells and neutrophils, in responders versus non-responders. Conclusions: Our findings suggest a potential advantage in PFS and OS with an increased presence of cytotoxic immune cells and genes associated with the recruitment and proliferation of these cell types before therapy.